Electrical distribution equipment such as power lines and associated switchgear components can suffer from various types of anomalies such as excessive heating, corona discharges and corona failures. These anomalies can be caused by faulty equipment such as dirty insulators, broken strands on a transmission line, or a cracked bushing on a distribution transformer. Early detection of such anomalies can reduce the risk of power failures or dangerous conditions such as downed power lines or fires.
Corona detection imaging systems have been developed based on image intensifiers with shortwave ultraviolet transparent windows and photocathodes such as bi-alkali or multi-alkali photocathodes with shortwave ultraviolet responsiveness. However, these systems typically generate low resolution images and are typically operated at a high operating gain that results in poor image quality. In particular, ultraviolet images captured by conventional corona detection imaging systems commonly include noise in the form of bright artifacts that occur continuously in random parts of the image. These artifacts can be difficult to distinguish from a corona event. It can therefore be difficult or impossible to perform automatic detection of corona events using conventional imaging systems, due to false alarms generated in response to image artifacts. It can also be difficult or impossible to distinguish between different types of electrical anomalies using the relatively low resolution images generated by conventional systems.
Moreover, because electrical distribution systems extend over large distances, it can be difficult to provide frequent manned inspections of electrical equipment, particularly in remote locations. It would therefore be desirable to be able to provide improved electrical equipment monitoring systems.